AI & Advanced Analytics Intern – Manufacturing & Energy Datasets

Boviet Solar is hiring an AI & Advanced Analytics Intern in Greenville, NC, to enhance solar manufacturing using data and AI. Candidates should have a background in Python and data engineering. Responsibilities include developing AI models, building ETL pipelines, conducting data analysis, and collaborating with engineering teams. This internship offers hands-on experience in renewable energy and mentorship from industry professionals.
Job Summary:

Boviet Solar is seeking a passionate and technically skilled AI & Advanced Analytics Intern to support our mission of leveraging data and artificial intelligence to improve solar manufacturing operations. This role is ideal for candidates with a strong foundation in Python programming and data engineering who are eager to work on industrial-scale energy and manufacturing datasets. You will contribute to real-world use cases in areas such as yield optimization, predictive maintenance, energy consumption analysis, and quality control analytics.

Key Responsibilities:
• Develop AI/ML models to support manufacturing process optimization, defect detection, and yield improvement.
• Build scalable ETL pipelines to ingest, clean, and transform data from MES, SCADA, energy meters, and ERP systems (e.g., SAP ECC).
• Conduct exploratory data analysis on large-scale energy and manufacturing datasets using Python.
• Collaborate with engineering, production, and quality teams to define data-driven opportunities.
• Implement machine learning workflows for time-series prediction, anomaly detection, and classification problems.
• Develop Python scripts and use libraries like pandas, NumPy, scikit-learn, TensorFlow, or PyTorch for modeling.
• Visualize results through dashboards or notebooks to communicate insights effectively.
• Document model performance, assumptions, and engineering design decisions.

Required Skills & Qualifications:
• Currently pursuing a degree in Data Science, Computer Science, Engineering, or a related technical field.
• Proficient in Python and libraries used for data analysis and machine learning (pandas, scikit-learn, etc.).
• Understanding of data engineering concepts including ETL, APIs, and structured/unstructured data handling.
• Familiar with SQL and data query techniques.
• Strong analytical and problem-solving skills.
• Ability to work with large datasets from manufacturing systems such as MES and SCADA.
• Interest in applying AI in energy efficiency, manufacturing quality, and predictive maintenance.

Preferred Qualifications:
• Experience with cloud platforms (e.g., AWS, Azure, or GCP).
• Familiarity with time-series data processing and industrial data sources.
• Knowledge of SAP ECC modules such as PP, PM, and QM.
• Prior experience in solar or manufacturing domain is a plus.

What You'll Gain:
• Hands-on experience with high-impact AI/analytics projects in a renewable manufacturing setting.
• Exposure to real-world energy and operational datasets.
• Mentorship from data scientists, engineers, and manufacturing professionals.
• Insight into data-driven strategies in smart manufacturing and clean energy production.